The usual criterion for determining the line of best fit is.

The line of best fit is the line that minimizes the sum of the squared errors of prediction.
true
The sum of the squared errors of prediction.
false
The sum of the absolute deviations.
Although this criterion is occasionally used, it is not the usual criterion.
false
The line that goes through the most points.
questions/error.gif
The error is always the vertical distance to the line. It shows how far the predicted score is from the actual score.
In the graph, the error for the point specified by the arrow is represented by:

false
The length of the horizontal red line.
true
The length of the vertical blue line.
The line that minimizes the squared error is usually the same line that minimizes the absolute error.

The lines are usually similar but only identical under rare circumstances.
false
True
true
False